3D Measurement Device Parameter Optimization
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Solution Overview
Problem
The accuracy and productivity of workpiece identification in factory automation vary with different parameter settings for 3D measurement, making it difficult to manually set optimal values for parameters such as measurement frequency, sensor movement speed, and angle, leading to inconsistent results.
Innovation Solution
A measurement device and method that includes a 3D sensor, parameter setter, drive controller, sensor controller, registration processor, storage, input unit, and output unit, which automatically sets and adjusts parameters within a predetermined range to achieve user-defined conditions for 3D measurement data, allowing for easy selection of optimal parameter combinations based on priority conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the range sensor is moved slower and measures point clouds more times, then workpiece identification accuracy is improved, but measurement time increases and productivity decreases
Solution Approach 1:
The system pre-calculates and stores optimal parameter combinations in a lookup table before actual measurement. By performing the computational work in advance and organizing results for quick retrieval, the system can rapidly provide accurate parameter recommendations without real-time complex calculations, thus improving both accuracy and productivity
2Productivity
If the range sensor is moved faster and measures point clouds fewer times, then productivity is improved, but workpiece identification accuracy decreases
Solution Approach 1:
The system incorporates user feedback by allowing selection from multiple recommended parameter combinations based on priority conditions. This feedback mechanism enables the system to adapt to specific measurement requirements while maintaining optimal accuracy and productivity balance through iterative refinement of parameter selection
3Measurement precision
If multiple parameters are manually adjusted to optimize workpiece identification, then identification accuracy can be improved, but the complexity of parameter setting increases
Solution Approach 1:
The system automatically generates and recommends optimal parameter combinations based on pre-stored data and user-defined priority conditions, eliminating the need for manual parameter tuning. The system serves itself by providing intelligent recommendations that users can directly apply, significantly reducing setting complexity while maintaining high identification accuracy
Data Source
AI summary
Values of parameters specifying conditions for obtaining 3D measurement data representing a measurement object are output as values satisfying a condition designated by a user. The technique includes setting and changing, within a predetermined range, values of parameters specifying conditions for obtaining 3D measurement data represented by 3D coordinates indicating points on a surface of the measurement object, measuring the measurement object to obtain 3D data sets representing the measurement object based on the parameter values resulting from the setting or the change, registering the 3D data sets, storing an identification result of the measurement object based on 3D data obtained through the registration in association with the parameter values, receiving, from a user, designation of a priority condition for obtaining 3D measurement data, and outputting a combination(s) of values of parameters satisfying the priority condition based on association between identification results of the measurement object and the parameter values.